Dr Lorenzo Magazzini

MEG Bioinformatic Officer

Research summary

My research interests focus on neuronal oscillations in the gamma frequency range. During my PhD, I developed a novel method to estimate the reliability of peak frequency measures obtained from visual cortex non-invasively with Magnetoencephalography (MEG). I investigated the changes in visual gamma oscillations induced by pharmacological manipulation of the GABAergic system and by modulation of cognitive functions such as spatial attention. I also investigated the inter-individual variability of the gamma oscillatory parameters in large samples of healthy individuals (100+), combining datasets recorded with different MEG systems at multiple MEG centres in the UK.

Currently, my work is aimed at establishing a multi-site database of normative MEG data (600+ individuals) collected across eight MEG laboratories in the UK, developing common analysis and management pipelines for mining this resource. This database will represent one of the largest and most valuable electrophysiological data cohorts to be freely available to the international research community.

Selected publications (2014 onwards)

Full list of publications

Research topics and related papers

My research interests focus on neuronal oscillations in the gamma frequency range. During my PhD, I developed a novel method to estimate the reliability of peak frequency measures obtained from visual cortex non-invasively with Magnetoencephalography (MEG). I investigated the changes in visual gamma oscillations induced by pharmacological manipulation of the GABAergic system and by modulation of cognitive functions such as spatial attention. I also investigated the inter-individual variability of the gamma oscillatory parameters in large samples of healthy individuals (100+), combining datasets recorded with different MEG systems at multiple MEG centres in the UK.

Currently, my work is aimed at establishing a multi-site database of normative MEG data (600+ individuals) collected across eight MEG laboratories in the UK, developing common analysis and management pipelines for mining this resource. This database will represent one of the largest and most valuable electrophysiological data cohorts to be freely available to the international research community.